Wed, 26 Aug 2026

Package fitPS updated to version 1.1.4 with previous version 1.0.6 dated 2026-06-10

Title: Fit Probability Models to Forensic Survey Data
Description: Fits probability models to P- and S-type count data arising from forensic surveys of clothing for the background presence of glass, paint, and related trace material. Built-in models include zeta, zero-inflated zeta, and logarithmic distributions, with a public extension interface for additional models. Inference is available by maximum likelihood, parametric Bayesian methods, the ordinary nonparametric bootstrap, and Rubin's Bayesian Bootstrap. The clothing-survey setting is described by Coulson, Buckleton, Gummer, and Triggs (2001) <doi:10.1016/S1355-0306(01)71847-3>.
Author: James Curran [aut, cre]
Maintainer: James Curran <j.curran@auckland.ac.nz>

Diff between fitPS versions 1.0.6 dated 2026-06-10 and 1.1.4 dated 2026-08-26

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More information about fitPS at CRAN
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Package finnts updated to version 0.7.0 with previous version 0.6.0 dated 2025-09-04

Title: Microsoft Finance Time Series Forecasting Framework
Description: Automated time series forecasting developed by Microsoft Finance. The Microsoft Finance Time Series Forecasting Framework, aka Finn, can be used to forecast any component of the income statement, balance sheet, or any other area of interest by finance. Any numerical quantity over time, Finn can be used to forecast it. While it can be applied outside of the finance domain, Finn was built to meet the needs of financial analysts to better forecast their businesses within a company, and has a lot of built in features that are specific to the needs of financial forecasters. Happy forecasting!
Author: Mike Tokic [aut, cre] , Aadharsh Kannan [aut]
Maintainer: Mike Tokic <mftokic@gmail.com>

Diff between finnts versions 0.6.0 dated 2025-09-04 and 0.7.0 dated 2026-08-26

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Package LLMing updated to version 1.3.0 with previous version 1.2.1 dated 2026-03-27

Title: Large Language Model (LLM) Tools for Psychological Text Analysis
Description: A collection of large language model (LLM) text analysis methods designed with psychological data in mind. Currently, LLMing (aka "lemming") includes a text anomaly detection method based on the angle-based subspace approach described by Zhang, Lin, and Karim (2015) and a text generation method. <doi:10.1016/j.ress.2015.05.025>.
Author: Lindley Slipetz [aut, cre], Teague Henry [aut], Siqi Sun [ctb]
Maintainer: Lindley Slipetz <ddj6tu@virginia.edu>

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Package graphicalMCP updated to version 0.3.0 with previous version 0.2.9 dated 2026-03-21

Title: Graphical Multiple Comparison Procedures
Description: Multiple comparison procedures (MCPs) control the familywise error rate in clinical trials. Graphical MCPs include many commonly used procedures as special cases; see Bretz et al. (2011) <doi:10.1002/bimj.201000239>, Lu (2016) <doi:10.1002/sim.6985>, and Xi et al. (2017) <doi:10.1002/bimj.201600233>. This package is a low-dependency implementation of graphical MCPs which allow mixed types of tests. It also includes power simulations and visualization of graphical MCPs.
Author: Dong Xi [aut, cre], Ethan Brockmann [aut], Gilead Sciences, Inc. [cph, fnd]
Maintainer: Dong Xi <dong.xi1@gilead.com>

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Package FLSSS updated to version 9.2.9 with previous version 9.2.8 dated 2025-06-22

Title: Mining Rigs for Problems in the Subset Sum Family
Description: Specialized solvers for combinatorial optimization problems in the Subset Sum family. The solvers differ from the mainstream in the options of (i) restricting subset size, (ii) bounding subset elements, (iii) mining real-value multisets with predefined subset sum errors, (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The multi-threaded framework for the latter offers exact algorithms to the multidimensional Knapsack and the Generalized Assignment problems. Historical updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) option of mapping floating-point instance to [...truncated...]
Author: Charlie Wusuo Liu [aut, cre]
Maintainer: Charlie Wusuo Liu <liuwusuo@gmail.com>

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Package bluertopo updated to version 0.0.2 with previous version 0.0.1 dated 2026-08-04

Title: Download and Extract BlueTopo Bathymetry with Terra
Description: Discovers, downloads, verifies, and opens bathymetry assets from the National Oceanic and Atmospheric Administration (NOAA) BlueTopo product for user supplied areas of interest. The package keeps source files intact by default, uses 'terra' for spatial data access, supports explicit native-resolution selection policies, and records provenance for reproducible extraction workflows. It accesses the NOAA BlueTopo web service at <https://noaa-ocs-nationalbathymetry-pds.s3.amazonaws.com/> and references product documentation at <https://nauticalcharts.noaa.gov/data/bluetopo.html>.
Author: Elvin Cordero [aut, cre, cph]
Maintainer: Elvin Cordero <elvin.cordero@seamountgeo.com>

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Package DataSpaceR updated to version 1.0.2 with previous version 1.0.1 dated 2026-08-04

Title: Interface to 'the CAVD DataSpace'
Description: Provides a convenient API interface to access immunological data within 'the CAVD DataSpace'(<https://dataspace.cavd.org>), a data sharing and discovery tool that facilitates exploration of HIV immunological data from pre-clinical and clinical HIV vaccine studies.
Author: Ju Yeong Kim [aut], Sean Hughes [rev], Jason Taylor [aut, cre], Helen Miller [aut], Kellie MacPhee [rev], CAVD DataSpace [cph]
Maintainer: Jason Taylor <jmtaylor@fredhutch.org>

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Package competitiontoolbox updated to version 0.7.4 with previous version 0.7.1 dated 2022-08-25

Title: A Graphical User Interface for Antitrust and Trade Practitioners
Description: A graphical user interface for simulating the effects of mergers, tariffs, and quotas under an assortment of different economic models. The interface is powered by the 'Shiny' web application framework from 'RStudio'.
Author: Charles Taragin [aut, cre], Kenneth Rios [aut], Paulette Wolak [aut]
Maintainer: Charles Taragin <ctaragin+competitiontoolbox@gmail.com>

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Package clidatajp updated to version 0.5.3 with previous version 0.5.2 dated 2023-03-04

Title: Data from Japan Meteorological Agency
Description: Includes climate data from Japan Meteorological Agency ('JMA') <https://www.jma.go.jp/jma/indexe.html>. Can download climate data from 'JMA'.
Author: Toshikazu Matsumura [aut, cre]
Maintainer: Toshikazu Matsumura <matutosi@gmail.com>

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Package RClickhouse updated to version 0.6.12 with previous version 0.6.11 dated 2026-06-23

Title: 'Yandex Clickhouse' Interface for R with Basic 'dplyr' Support
Description: 'Yandex Clickhouse' (<https://clickhouse.com/>) is a high-performance relational column-store database to enable big data exploration and 'analytics' scaling to petabytes of data. Methods are provided that enable working with 'Yandex Clickhouse' databases via 'DBI' methods and using 'dplyr'/'dbplyr' idioms.
Author: Christian Hotz-Behofsits [aut, cre], Daniel Winkler [aut], Luca Rauchenberger [aut], Peter Knaus [aut], Clemens Danninger [aut], Daria Yudaeva [aut], Simon Stiebellehner [aut], Dan Egnor [aut], Vlad Losev [aut], Keith Ray [aut], Zhanyong Wan [aut], M [...truncated...]
Maintainer: Christian Hotz-Behofsits <christian.hotz-behofsits@wu.ac.at>

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Package OptimalBinningWoE updated to version 1.13.4 with previous version 1.13.3 dated 2026-08-23

Title: Optimal Binning and Weight of Evidence Framework for Modeling
Description: High-performance implementation of 37 optimal binning algorithms (16 categorical, 21 numerical) for Weight of Evidence ('WoE') transformation, credit scoring, and risk modeling. Includes advanced methods such as Mixed Integer Linear Programming ('MILP'), Genetic Algorithms, Simulated Annealing, and Monotonic Regression. Features automatic method selection based on Information Value ('IV') maximization, strict monotonicity enforcement, and efficient handling of large datasets via 'Rcpp'. Provides automated variable screening by Information Value strength and bin ordering, and generation of the equivalent 'SQL' 'CASE' expressions for in-database scoring. Fully integrated with the 'tidymodels' ecosystem for building robust machine learning pipelines. Based on methods described in Siddiqi (2006) <doi:10.1002/9781119201731> and Navas-Palencia (2020) <doi:10.48550/arXiv.2001.08025>.
Author: Jose Evandeilton Lopes [aut, cre, cph]
Maintainer: Jose Evandeilton Lopes <evandeilton@gmail.com>

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Package ofhsyn updated to version 0.1.3 with previous version 0.1.1 dated 2026-06-09

Title: Synthetic Our Future Health Data Generator
Description: Generates synthetic Our Future Health cohort datasets for method development, including participant, questionnaire, clinic measurements, outpatient, inpatient, emergency, mortality, primary care medication, and geography outputs. Supports reproducible generation with configurable cohort size and user-defined International Classification of Diseases, Tenth Revision (ICD-10), Office of Population Censuses and Surveys Classification of Interventions and Procedures, version 4 (OPCS-4), and British National Formulary (BNF) code pools.
Author: Hannah Nicholls [aut, cre]
Maintainer: Hannah Nicholls <hlnichollsdev@outlook.com>

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Package moveEZ updated to version 1.3.0 with previous version 1.2.0 dated 2026-05-13

Title: Animated Biplots
Description: Create animated biplots that enables dynamic visualisation of temporal or sequential changes in multivariate data by animating a single biplot across the levels of a time variable. It builds on objects from the 'biplotEZ' package, Lubbe S, le Roux N, Nienkemper-Swanepoel J, Ganey R, Buys R, Adams Z, Manefeldt P (2024) <doi:10.32614/CRAN.package.biplotEZ>, allowing users to create animated biplots that reveal how both samples and variables evolve over time.
Author: Raeesa Ganey [aut, cre, cph] , Johane Nienkemper-Swanepoel [aut, cph]
Maintainer: Raeesa Ganey <raeesa.ganey@wits.ac.za>

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Package mispitools updated to version 2.0.1 with previous version 2.0.0 dated 2026-08-25

Title: Missing Person Identification Tools
Description: A comprehensive toolkit for missing person identification combining genetic and non-genetic evidence within a Bayesian framework. Computes likelihood ratios (LRs) for DNA profiles, biological sex, age, hair color, and birthdate evidence. Provides decision analysis tools including optimal LR thresholds, error rate calculations, and ROC curve visualization. Includes interactive Shiny applications for exploring evidence combinations. For methodological details see Marsico et al. (2023) <doi:10.1016/j.fsigen.2023.102891> and Marsico, Vigeland et al. (2021) <doi:10.1016/j.fsigen.2021.102519>.
Author: Franco Marsico [aut, cre] , Suisei Nakagawa [aut]
Maintainer: Franco Marsico <franco.lmarsico@gmail.com>

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Package MethScope updated to version 1.0.4 with previous version 1.0.3 dated 2026-06-16

Title: Ultra-Fast Analysis of Sparse DNA Methylome via Recurrent Pattern Encoding
Description: Methods for analyzing DNA methylation data via Most Recurrent Methylation Patterns (MRMPs). Supports cell-type annotation, spatial deconvolution, unsupervised clustering, and cancer cell-of-origin inference. Includes C-backed summaries for YAME ".cg/.cm" files (overlap counts, log2 odds ratios, beta/depth aggregation), an XGBoost classifier, NNLS deconvolution, and plotting utilities. Scales to large spatial and single-cell methylomes and is robust to extreme sparsity.
Author: Hongxiang Fu [aut, cre] , Wanding Zhou [cph, fnd], The SAMtools/HTSlib authors [ctb, cph] , Attractive Chaos [ctb, cph] )
Maintainer: Hongxiang Fu <fhx@seas.upenn.edu>

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Package eigencore updated to version 1.0.3 with previous version 1.0.2 dated 2026-07-25

Title: Certified Partial Eigenvalue and Singular Value Computation
Description: Computes the top-k singular triplets or eigenpairs of large sparse and structured matrices: the computation behind principal component analysis on big sparse data, spectral embeddings, and low-rank approximation. Every result carries a numerical certificate with residuals, a backward-error bound, orthogonality loss, and a pass/fail flag, and bounds that can only be estimated are reported as such rather than passed. Centered, scaled, and composed operators are solved through native 'C++' kernels without forming dense matrices. Drop-in replacements for the 'RSpectra' interface are included.
Author: Bradley Buchsbaum [aut, cre, cph]
Maintainer: Bradley Buchsbaum <brad.buchsbaum@gmail.com>

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Package baseballr updated to version 2.0.0 with previous version 1.6.0 dated 2024-01-16

Title: Acquiring and Analyzing Baseball Data
Description: Provides numerous utilities for acquiring and analyzing baseball data from online sources such as 'Baseball Reference' <https://www.baseball-reference.com/>, 'FanGraphs' <https://www.fangraphs.com/>, and the 'MLB Stats' API <https://www.mlb.com/>.
Author: Bill Petti [aut], Saiem Gilani [aut, cre] , Ben Baumer [ctb], Ben Dilday [ctb], Robert Frey [ctb], Camden Kay [ctb], baseballr authors [cph]
Maintainer: Saiem Gilani <saiem.gilani@gmail.com>

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 man/mlb_player_game_stats_current.Rd                 |  244 -
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 tests/testthat/test-fg_batter_game_logs.R            |  567 ++--
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 tests/testthat/test-fg_guts.R                        |   35 
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 tests/testthat/test-fg_park.R                        |   35 
 tests/testthat/test-fg_park_hand.R                   |   35 
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 tests/testthat/test-label_statcast_imputed_data.R    |   59 
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 tests/testthat/test-load_umpire_ids.R                |   27 
 tests/testthat/test-metrics_team_consistency.R       |   26 
 tests/testthat/test-mlb_attendance.R                 |   51 
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 tests/testthat/test-mlb_divisions.R                  |   35 
 tests/testthat/test-mlb_draft.R                      |   90 
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 tests/testthat/test-mlb_draft_prospects.R            |  103 
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 tests/testthat/test-mlb_fielder_detail_types.R       |   27 
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 tests/testthat/test-mlb_game_content.R               |   35 
 tests/testthat/test-mlb_game_context_metrics.R       |   83 
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 tests/testthat/test-mlb_game_pace.R                  |   79 
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 tests/testthat/test-mlb_game_status_codes.R          |   31 
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 tests/testthat/test-mlb_game_types.R                 |   27 
 tests/testthat/test-mlb_game_wp.R                    |   29 
 tests/testthat/test-mlb_high_low_stats.R             |   89 
 tests/testthat/test-mlb_high_low_types.R             |   29 
 tests/testthat/test-mlb_hit_trajectories.R           |   27 
 tests/testthat/test-mlb_homerun_derby.R              |   91 
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 tests/testthat/test-mlb_job_types.R                  |   27 
 tests/testthat/test-mlb_jobs.R                       |   39 
 tests/testthat/test-mlb_jobs_datacasters.R           |   39 
 tests/testthat/test-mlb_jobs_official_scorers.R      |   39 
 tests/testthat/test-mlb_jobs_umpires.R               |   39 
 tests/testthat/test-mlb_languages.R                  |   27 
 tests/testthat/test-mlb_league.R                     |   81 
 tests/testthat/test-mlb_league_leader_types.R        |   27 
 tests/testthat/test-mlb_logical_events.R             |   27 
 tests/testthat/test-mlb_metrics.R                    |   27 
 tests/testthat/test-mlb_pbp.R                        |  315 +-
 tests/testthat/test-mlb_pbp_diff.R                   |  305 +-
 tests/testthat/test-mlb_pitch_codes.R                |   45 
 tests/testthat/test-mlb_pitch_types.R                |   27 
 tests/testthat/test-mlb_player_status_codes.R        |   27 
 tests/testthat/test-mlb_positions.R                  |   35 
 tests/testthat/test-mlb_probables.R                  |   29 
 tests/testthat/test-mlb_review_reasons.R             |   27 
 tests/testthat/test-mlb_roster_types.R               |   29 
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 tests/testthat/test-mlb_runner_detail_types.R        |   27 
 tests/testthat/test-mlb_schedule.R                   |   79 
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 tests/testthat/test-ncaa_team_player_stats.R         |   95 
 tests/testthat/test-ncaa_teams.R                     |   42 
 tests/testthat/test-sptrc_league_payrolls.R          |   49 
 tests/testthat/test-sptrc_team_active_payroll.R      |   56 
 tests/testthat/test-statcast_leaderboards.R          |   63 
 tests/testthat/test-statcast_search.R                |  119 
 709 files changed, 34161 insertions(+), 31217 deletions(-)

More information about baseballr at CRAN
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New package sportsR with initial version 0.1.0
Package: sportsR
Title: A Comprehensive Collection of Sports and Athletics Datasets
Version: 0.1.0
Maintainer: Renzo Caceres Rossi <arenzocaceresrossi@gmail.com>
Description: Offers a rich and diverse collection of datasets focused on sports, athletics, physical performance, and related disciplines. The package includes professional and amateur sports data covering team sports such as soccer, basketball, baseball, American football, volleyball, rugby, cricket, hockey, and handball, as well as individual sports including tennis, badminton, table tennis, golf, swimming, cycling, athletics, gymnastics, wrestling, boxing, martial arts, weightlifting, triathlon, rowing, canoeing, climbing, surfing, skiing, snowboarding, and motorsports. Datasets cover player and team performance, match statistics, tournament results, championship standings, Olympic and international competitions, rankings, player demographics, coaching and training, biomechanics, sports medicine, injuries, exercise physiology, fitness assessment, sports nutrition, wearable sensor measurements, talent identification, and sports analytics. Additional datasets include historical competitions, refer [...truncated...]
License: GPL-3
Language: en
URL: https://github.com/lightbluetitan/sportsr, https://lightbluetitan.github.io/sportsr/
BugReports: https://github.com/lightbluetitan/sportsr/issues
Encoding: UTF-8
LazyData: true
Suggests: ggplot2, testthat (>= 3.0.0), dplyr, knitr, rmarkdown
Depends: R (>= 4.1.0)
Imports: utils
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-21 00:22:16 UTC; Renzo
Author: Renzo Caceres Rossi [aut, cre]
Repository: CRAN
Date/Publication: 2026-08-26 20:20:02 UTC

More information about sportsR at CRAN
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Package SNMA updated to version 0.1.7 with previous version 0.1.5 dated 2026-02-04

Title: Stream Network Movement Analyses
Description: Calculating home ranges and movements of animals in complex stream environments is often challenging, and standard home range estimators do not apply. This package provides a series of tools for assessing movements in a stream network, such as calculating the total length of stream used, distances between points, and movement patterns over time. See Vignette for additional details. This package was originally released on 'GitHub' under the name 'SNM'. SNMA was developed for analyses in McKnight et al. (2025) <doi:10.3354/esr01442> which contains additional examples and information.
Author: Donald T. McKnight [aut, cre]
Maintainer: Donald T. McKnight <donald.mcknight@my.jcu.edu.au>

Diff between SNMA versions 0.1.5 dated 2026-02-04 and 0.1.7 dated 2026-08-26

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 4 files changed, 11 insertions(+), 8 deletions(-)

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Package pCalibrate updated to version 0.2-2 with previous version 0.2-1 dated 2020-03-19

Title: Bayesian Calibrations of p-Values
Description: Implements transformations of p-values to the smallest possible Bayes factor within the specified class of alternative hypotheses, as described in Held & Ott (2018, <doi:10.1146/annurev-statistics-031017-100307>). Covers several common testing scenarios such as z-tests, t-tests, likelihood ratio tests and the F-test.
Author: Manuela Ott [aut, cre] , Leonhard Held [aut]
Maintainer: Manuela Ott <manuela.c.ott@gmail.com>

Diff between pCalibrate versions 0.2-1 dated 2020-03-19 and 0.2-2 dated 2026-08-26

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 15 files changed, 1448 insertions(+), 1455 deletions(-)

More information about pCalibrate at CRAN
Permanent link

New package mvboxcox with initial version 0.1.4
Package: mvboxcox
Title: Bivariate Logistic Box-Cox Regression
Version: 0.1.4
Description: Fits bivariate logistic Box-Cox regression models for binary outcomes and positive continuous predictors. Transformation parameters are selected by cross-validated grid search with adaptive refinement and thin-plate spline smoothing. The package also provides prediction, empirical and sampling-weighted median effects, simulation tools, and sampling-weighted model fitting. The methodology extends the logistic Box-Cox approach of Xing et al. (2021) <doi:10.1002/cjs.11587>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: methods, stats, parallel, fields
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 20:50:38 UTC; xushiyu
Author: Shiyu Xu [aut], Xuekui Zhang [aut, cre]
Maintainer: Xuekui Zhang <ubcxzhang@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-26 20:10:02 UTC

More information about mvboxcox at CRAN
Permanent link

New package AgriFusionR with initial version 0.1.0
Package: AgriFusionR
Title: An Integration Framework for Agricultural Analytics
Version: 0.1.0
Description: Assembles agricultural analyses around a single unit of observation, the management unit within a season, and keeps climate, soil and remote-sensing covariates aligned to it. Covariates are aggregated over phenological windows derived from accumulated growing degree days rather than calendar months, following McMaster and Wilhelm (1997) <doi:10.1016/S0168-1923(97)00027-0>. Models are validated with spatial resampling by default, since random cross-validation inflates apparent skill when observations are spatially autocorrelated, as shown by Roberts and others (2017) <doi:10.1111/ecog.02881>. Prediction intervals use split conformal inference after Lei and others (2018) <doi:10.1080/01621459.2017.1307116>. Data sources and learning algorithms are supplied through registries so that new providers and methods can be added without modifying the package.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, stats, utils
Suggests: testthat (>= 3.0.0), ranger, xgboost, Cubist, glmnet, kernlab, mgcv, treeshap, nasapower, chirps, daymetr, geodata, terra, agridat, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/mqfarooqi1/AgriFusionR
BugReports: https://github.com/mqfarooqi1/AgriFusionR/issues
NeedsCompilation: no
Packaged: 2026-08-20 23:18:42 UTC; faroo
Author: Muhammad Farooqi [aut, cre]
Maintainer: Muhammad Farooqi <mqfarooqi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-26 20:20:08 UTC

More information about AgriFusionR at CRAN
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New package textclassificationtutorial with initial version 0.1.2
Package: textclassificationtutorial
Title: Reproducible Text Classification Workflows
Version: 0.1.2
Description: Dependency-light tools and tutorials for teaching reproducible text classification. The package covers HTML text extraction, sentence segmentation, text preprocessing, document-term matrices, TF-IDF, keyword extraction, cosine similarity, stratified cross-validation, classification metrics, and a multinomial Naive Bayes classifier. It modernizes the code accompanying Kobayashi, V. B., Berkers, H. A., Mol, S. T. Kismihok, G., and Den Hartog, D. N. (2017) <doi:10.1177/1094428117719322> The package replaces the original scripts in the paper.
License: Apache License (>= 2)
URL: https://github.com/vkobayashi/textclassificationtutorial
BugReports: https://github.com/vkobayashi/textclassificationtutorial/issues
Depends: R (>= 4.1.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), xml2
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-20 21:22:17 UTC; vladimerkobayashi
Author: Vladimer Kobayashi [aut, cre], Stefan Mol [aut], Gabor Kismihok [aut]
Maintainer: Vladimer Kobayashi <vladimer.kobayashi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-26 19:30:02 UTC

More information about textclassificationtutorial at CRAN
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Package irtbem2pl updated to version 1.0.1 with previous version 1.0.0 dated 2026-06-08

Title: Marginalized Bayesian Item Parameter Estimation, 2pl Model IRT
Description: Estimates item parameters of the two-parameter logistic (2PL) model in Item Response Theory (IRT) using the marginal Bayesian modal estimation via the Expectation-Maximization (EM) algorithm. The package calibrates item discrimination and difficulty parameters, yielding results comparable to software like 'BILOG-MG'.
Author: Juan Luis Legorreta Torres [aut, cre]
Maintainer: Juan Luis Legorreta Torres <jlegorreta2002@yahoo.com.mx>

Diff between irtbem2pl versions 1.0.0 dated 2026-06-08 and 1.0.1 dated 2026-08-26

 DESCRIPTION           |    8 ++--
 MD5                   |    9 +++--
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 R/LikelihoodInfo2pl.R |   82 +++++++++++++++++++++++++++++---------------------
 R/irt2pl.R            |   58 ++++++++++++++++++++++++-----------
 R/irtchek2pl.R        |   65 ++++++++++++++-------------------------
 6 files changed, 120 insertions(+), 102 deletions(-)

More information about irtbem2pl at CRAN
Permanent link

New package gpciLindApproxProgII with initial version 0.1.0
Package: gpciLindApproxProgII
Title: Lindley Approximation for Capability Indices under Progressive Censoring
Version: 0.1.0
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Description: Implements Bayesian parameter and Generalized Process Capability Indices (GPCIs) estimation using the Lindley approximation method (Lindley, 1980 <doi:10.2307/2345271>) under progressive Type-II censored data (Balakrishnan & Aggarwala, 2000 <doi:10.1007/978-1-4612-1334-5>). Evaluates point estimates and posterior expectations for classical and non-normal capability indices, including Cpy (Maiti et al., 2010 <doi:10.1080/16843703.2010.11673233>), Spmk (Dey & Saha, 2019 <doi:10.1007/s41872-019-00081-4>), CpTk (Saha et al., 2019), Cpc (Saha et al., 2022 <doi:10.1080/02664763.2021.1971632>), CNpmc (Alotaibi et al., 2022 <doi:10.1155/2022/3135264>), CNpmkc (Saha et al., 2024 <doi:10.1142/S021853932450013X>), CNpk (Saha et al., 2018 <doi:10.1080/21681015.2018.1437793>), and Vannman's Cp(u,v) family (Vannman, 1995 <doi:10.1111/j.1467-9574.1995.tb01472.x>). Calculates point estimates, bias, mean squared error (MSE), Bayes risk under [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, ggplot2, numDeriv, boot, coda
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 22:06:37 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Sumit Kumar [aut], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Repository: CRAN
Date/Publication: 2026-08-26 19:50:02 UTC

More information about gpciLindApproxProgII at CRAN
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New package enrollcast with initial version 0.1.0
Package: enrollcast
Title: Project School Enrollment with Grade Progression Ratios
Version: 0.1.0
Description: Projects school enrollment using the cohort survival / grade progression ratio method described in Webster (1970) <doi:10.1080/00220973.1970.11011238>, implemented as a matrix projection. Works at any level of aggregation and any number of grades. Provides functions to compute progression ratios from historical grade-level enrollment and to project future enrollment forward an arbitrary horizon.
License: MIT + file LICENSE
URL: https://rorylawless.r-universe.dev/enrollcast, https://github.com/localopen/enrollcast, https://localopen.github.io/enrollcast/
BugReports: https://github.com/localopen/enrollcast/issues
Depends: R (>= 4.0)
Imports: cli (>= 3.4.0), rlang (>= 1.0.0), stats
Suggests: knitr, rmarkdown, testthat (>= 3.2.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-20 23:13:15 UTC; rory
Author: Rory Lawless [aut, cre, cph]
Maintainer: Rory Lawless <rory@rorylawless.com>
Repository: CRAN
Date/Publication: 2026-08-26 20:00:02 UTC

More information about enrollcast at CRAN
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New package cantrends with initial version 0.1.0
Package: cantrends
Title: Fit Segmented Regression Models
Version: 0.1.0
Description: Estimates piecewise linear spline models for assessing temporal trends in cancer incidence and mortality rates. Provides tools for identifying and reporting knot locations, annual percent changes (APCs), and average annual percent changes (AAPCs), facilitating the analysis and communication of changes in cancer rates over time.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: broom, carrier (>= 0.3.0), cli, dplyr, glue, lspline, mirai (>= 2.5.1), purrr (>= 1.1.0), rlang, tibble
URL: https://github.com/mattwarkentin/cantrends
BugReports: https://github.com/mattwarkentin/cantrends/issues
NeedsCompilation: no
Packaged: 2026-08-20 23:00:05 UTC; matt
Author: Matthew T. Warkentin [aut, cre, cph] , John Hutchinson [ctb], Yibing Ruan [ctb]
Maintainer: Matthew T. Warkentin <matthew.warkentin@ucalgary.ca>
Repository: CRAN
Date/Publication: 2026-08-26 20:00:08 UTC

More information about cantrends at CRAN
Permanent link

New package AISanalyze with initial version 3.1.2
Package: AISanalyze
Title: Processing and Analyzing AIS Vessel Tracking Data
Version: 3.1.2
Description: Processes Automatic Identification System (AIS) vessel tracking data, including travel estimation, trajectory correction, interpolation, extraction, and summarising vessel information. The package is designed to facilitate reproducible analyses of maritime traffic in ecological, environmental, and marine spatial planning applications. For more details see <https://remip48.github.io/AISanalyze/>.
License: MIT + file LICENSE
Depends: R(>= 4.2.0)
Imports: dplyr, sf, purrr, stats, stringr, doParallel, parallel, foreach, assertthat, data.table, magrittr
Suggests: knitr, units, lubridate, rmarkdown, testthat
URL: https://github.com/remip48/AISanalyze, https://remip48.github.io/AISanalyze/
BugReports: https://github.com/remip48/AISanalyze/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 21:25:59 UTC; 234028
Author: Remi Pigeault [aut, cre]
Maintainer: Remi Pigeault <remi.pigeault@tiho-hannover.de>
Repository: CRAN
Date/Publication: 2026-08-26 19:40:01 UTC

More information about AISanalyze at CRAN
Permanent link

Package L0ggm updated to version 0.1.2 with previous version 0.1.1 dated 2026-07-06

Title: Smooth L0 Penalty Approximations for Gaussian Graphical Models
Description: Provides smooth approximations to the L0 norm penalty for estimating sparse Gaussian graphical models (GGMs). Network estimation is performed using the Local Linear Approximation (LLA) framework (Fan & Li, 2001 <doi:10.1198/016214501753382273>; Zou & Li, 2008 <doi:10.1214/009053607000000802>) with five penalty functions: arctangent (Wang & Zhu, 2016 <doi:10.1155/2016/6495417>), EXP (Wang, Fan, & Zhu, 2018 <doi:10.1007/s10463-016-0588-3>), Gumbel, Log (Candes, Wakin, & Boyd, 2008 <doi:10.1007/s00041-008-9045-x>), and Weibull. Adaptive penalty parameters for EXP, Gumbel, and Weibull are estimated via maximum likelihood, and model selection uses information criteria including AIC, BIC, and EBIC (Extended BIC). Simulation functions generate multivariate normal data from GGMs with stochastic block model or small-world (Watts-Strogatz) network structures.
Author: Alexander Christensen [aut, cre] , Jeongwon Choi [ctb] , John Fox [cph, ctb] , Yves Rosseel [cph, ctb] , Alan Genz [cph, ctb] in polychoric_matrix.c, translated via the pbivnorm R package), David Blackman [ctb] , Sebastiano Vigna [ctb] , John Burkar [...truncated...]
Maintainer: Alexander Christensen <alexpaulchristensen@gmail.com>

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New package ggnext with initial version 0.1.0
Package: ggnext
Title: A Next-Generation Grammar of Graphics
Version: 0.1.0
Description: An implementation of the Grammar of Graphics described by Wilkinson (2005, ISBN:978-0-387-24544-7), built on 'S7' classes. The familiar grammar vocabulary of aesthetics, geometries, statistics, scales, coordinates, facets and themes composed with '+' is preserved; every constructor that takes an argument also accepts a plot as the first argument of a native pipe ('|>') stage, so the two styles are interchangeable. The package is extended with built-in interactivity, animation, an exact-data export, a plot linter that flags common statistical-graphics mistakes before a figure ships, and a catalogue covering layout diagrams (Sankey, treemap, network, radar), machine-learning diagnostics (SHAP, receiver operating characteristic, calibration, partial dependence) and clinical reporting (Kaplan-Meier, forest, swimmer, CONSORT). Static output is written to Scalable Vector Graphics; interactive output is a self-contained 'HTML' document using a canvas element and vanilla 'JavaScript'. Both [...truncated...]
URL: https://itsmdivakaran.github.io/ggnext/, https://github.com/itsmdivakaran/ggnext
BugReports: https://github.com/itsmdivakaran/ggnext/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: S7, grDevices, stats, utils
Suggests: knitr, markdown, rmarkdown, testthat (>= 3.0.0), xml2
NeedsCompilation: no
Packaged: 2026-08-20 19:17:15 UTC; maheshdivakaran
Author: Mahesh Divakaran [aut, cre, cph]
Maintainer: Mahesh Divakaran <itsmdivakaran@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-26 18:40:02 UTC

More information about ggnext at CRAN
Permanent link

Package csemTools updated to version 0.2.1 with previous version 0.1.4 dated 2026-07-29

Title: Conditional Standard Error of Measurement Tools for Test Scores
Description: Compute and compare conditional standard errors of measurement (CSEM) across score distributions using methods from classical test theory. Includes approaches for smoothing, bootstrapped CSEM, standardized CSEM, CSEM for scale scores, and assessment of properties of split-half scores. Also supports comparison with global standard errors derived from reliability coefficients and graphical visualization of CSEM curves and relative precision across observed score ranges. Some of these implemented methods are based on work by Lord (1955) <doi:10.1002/j.2333-8504.1955.tb00054.x>, Feldt and Qualls (1996) <doi:10.1111/j.1745-3984.1996.tb00486.x>, McNeish and Dumas (2025) <doi:10.3758/s13428-025-02611-8>.
Author: Cesar Merino-Soto [aut, cre]
Maintainer: Cesar Merino-Soto <sikayax@yahoo.com.ar>

Diff between csemTools versions 0.1.4 dated 2026-07-29 and 0.2.1 dated 2026-08-26

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Package bayesics updated to version 3.0.1 with previous version 3.0.0 dated 2026-07-13

Title: Bayesian Analyses for One- and Two-Sample Inference and Regression Methods
Description: Perform fundamental analyses using Bayesian parametric and non-parametric inference (regression, anova, 1 and 2 sample inference, non-parametric tests, etc.). (Practically) no Markov chain Monte Carlo (MCMC) is used; all exact finite sample inference is completed via closed form solutions or else through posterior sampling automated to ensure precision in interval estimate bounds. Diagnostic plots for model assessment, and key inferential quantities (point and interval estimates, probability of direction, region of practical equivalence, and Bayes factors) and model visualizations are provided. Bayes factors are computed either by the Savage Dickey ratio given in Dickey (1971) <doi:10.1214/aoms/1177693507> or by Chib's method as given in <doi:10.1080/01621459.1995.10476635>. Interpretations are from Kass and Raftery (1995) <doi:10.1080/01621459.1995.10476572>. ROPE bounds are based on discussions in Kruschke (2018) <doi:10.1177/2515245918771304>. Methods for d [...truncated...]
Author: Daniel K. Sewell [aut, cre, cph] , Alan Arakkal [aut]
Maintainer: Daniel K. Sewell <daniel-sewell@uiowa.edu>

Diff between bayesics versions 3.0.0 dated 2026-07-13 and 3.0.1 dated 2026-08-26

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Package quickcode updated to version 1.2.0 with previous version 1.1.0 dated 2026-08-03

Title: Quick and Essential 'R' Tricks for Better Scripts
Description: The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to improve your scripts. Improve the quality and reproducibility of 'R' scripts.
Author: Obinna Obianom [aut, cre], Brice Richard [aut]
Maintainer: Obinna Obianom <idonshayo@gmail.com>

Diff between quickcode versions 1.1.0 dated 2026-08-03 and 1.2.0 dated 2026-08-26

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Package multilevLCA updated to version 2.1.5 with previous version 2.1.4 dated 2026-03-24

Title: Estimates and Plots Single-Level and Multilevel Latent Class Models
Description: Efficiently estimates single- and multilevel latent class models with covariates, allowing for output visualization in all specifications. For more technical details, see Lyrvall et al. (2025) <doi:10.1080/00273171.2025.2473935>.
Author: Roberto Di Mari [aut, cre], Johan Lyrvall [aut], Zsuzsa Bakk [ctb], Jennifer Oser [ctb], Jouni Kuha [ctb]
Maintainer: Roberto Di Mari <roberto.dimari@unict.it>

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Package litedown updated to version 0.11 with previous version 0.10 dated 2026-07-11

Title: A Lightweight Version of R Markdown
Description: Render R Markdown to Markdown (without using 'knitr'), and Markdown to lightweight HTML or 'LaTeX' documents with the 'commonmark' package (instead of 'Pandoc'). Some missing Markdown features in 'commonmark' are also supported, such as raw HTML or 'LaTeX' blocks, 'LaTeX' math, superscripts, subscripts, footnotes, element attributes, and appendices, but not all 'Pandoc' Markdown features are (or will be) supported. With additional JavaScript and CSS, you can also create HTML slides and articles. This package can be viewed as a trimmed-down version of R Markdown and 'knitr'. It does not aim at rich Markdown features or a large variety of output formats (the primary formats are HTML and 'LaTeX'). Book and website projects of multiple input documents are also supported.
Author: Yihui Xie [aut, cre] , Tim Taylor [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between litedown versions 0.10 dated 2026-07-11 and 0.11 dated 2026-08-26

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Package autograph updated to version 1.2.1 with previous version 1.1.2 dated 2026-07-31

Title: Automatic Plotting and Theming of Many Graphs
Description: Visual exploration and presentation of networks should not be difficult. This package includes functions for plotting networks and network-related metrics with sensible and pretty defaults. It includes 'ggplot2'-based plot methods for many popular network package classes. It also includes some novel layout algorithms, and options for straightforward, consistent themes.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

Diff between autograph versions 1.1.2 dated 2026-07-31 and 1.2.1 dated 2026-08-26

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Package DiscreteTests updated to version 0.5.0 with previous version 0.4.1 dated 2026-05-28

Title: Vectorised Computation of P-Values and Their Supports for Several Discrete Statistical Tests
Description: Provides vectorised functions for computing p-values of various common discrete statistical tests, as described e.g. in Agresti (2002) <doi:10.1002/0471249688>, including their distributions. Exact and approximate computation methods are provided. For exact ones, several procedures of determining two-sided p-values are included, which are outlined in more detail in Hirji (2006) <doi:10.1201/9781420036190>.
Author: Florian Junge [cre, aut] , Christina Kihn [aut], Sebastian Doehler [ctb] , Guillermo Durand [ctb]
Maintainer: Florian Junge <diso.fbmn@h-da.de>

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Package ALDEx3 updated to version 1.3.1 with previous version 1.2.0 dated 2026-07-15

Title: Linear Models for Sequence Count Data
Description: Provides scalable generalized linear and mixed effects models tailored for sequence count data analysis (e.g., analysis of 16S or RNA-seq data). Uses Dirichlet-multinomial sampling to quantify uncertainty in relative abundance or relative expression conditioned on observed count data. Implements scale models as a generalization of normalizations which account for uncertainty in scale (e.g., total abundances) as described in Nixon et al. (2025) <doi:10.1186/s13059-025-03609-3> and McGovern et al. (2025) <doi:10.1101/2025.08.05.668734>.
Author: Justin Silverman [aut, cre], Greg Gloor [aut], Kyle McGovern [aut, ctb]
Maintainer: Justin Silverman <JustinSilverman@psu.edu>

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Package metalite.sl updated to version 0.1.3 with previous version 0.1.2 dated 2026-06-12

Title: Subject-Level Analysis Using 'metalite'
Description: Analyzes subject-level data in clinical trials using the 'metalite' data structure. The package simplifies the workflow to create production-ready tables, listings, and figures discussed in the subject-level analysis chapters of "R for Clinical Study Reports and Submission" by Zhang et al. (2022) <https://r4csr.org/>.
Author: Yujie Zhao [aut, cre], Benjamin Wang [aut], Hiroaki Fukuda [aut], PoYao Niu [aut], Nan Xiao [aut], Jeetener Chauhan [ctb], Li Ma [ctb], Chen Wang [ctb], Merck Sharp & Dohme Corp [cph]
Maintainer: Yujie Zhao <yujie.zhao@merck.com>

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Package longitree updated to version 1.0.2 with previous version 1.0.1 dated 2026-05-16

Title: Decision Tree Analysis for Longitudinal Measurement Data
Description: Implements tree-based methods for longitudinal data. The package constructs decision trees that evaluate both the main effect of a covariate and its interaction with time through a weighted splitting criterion. It supports single-tree construction, bootstrap-based multiple-tree selection, and tree visualisation. For methodological details, see Obata and Sugimoto (2026) <doi:10.1007/s11634-025-00665-2>.
Author: Ryoto Obata [aut, cre], Tomoyuki Sugimoto [aut]
Maintainer: Ryoto Obata <ryoto.obata@gmail.com>

Diff between longitree versions 1.0.1 dated 2026-05-16 and 1.0.2 dated 2026-08-26

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Package ctreeMI updated to version 1.0.1 with previous version 1.0.0 dated 2026-07-27

Title: Conditional Inference Trees with Stacked Multiple Imputation
Description: Implements the stacked-imputation workflow for conditional inference trees ('ctree') described in Sherlock et al. (2026) <doi:10.1080/00273171.2026.2661244>. When data contain missing values, multiply imputed datasets (e.g., from 'mice') are stacked vertically and a single 'ctree' is fit on the combined data. To correct for the artificially inflated sample size introduced by stacking, every node-level test statistic is divided by the number of imputations M, the node-level p-values are recomputed from the chi-squared reference distribution 'ctree' uses (including its multiplicity adjustment across candidate splitting variables), and the tree is compressed bottom-up (the Stack/M correction). Degrees of freedom are derived for each node and each candidate variable, so univariate, bivariate and higher-dimensional outcomes are all handled, as are unordered factor predictors, whose degrees of freedom depend on how many levels remain in a node. The result is a single interpretable tree [...truncated...]
Author: Phillip Sherlock [aut, cre]
Maintainer: Phillip Sherlock <phillip.sherlock@ufl.edu>

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Package BAT updated to version 2.11.3 with previous version 2.11.1 dated 2026-03-30

Title: Biodiversity Assessment Tools
Description: Includes algorithms to assess alpha and beta diversity in all their dimensions (taxonomic, phylogenetic and functional). It allows performing a number of analyses based on species identities/abundances, phylogenetic/functional distances, trees, convex-hulls or kernel density n-dimensional hypervolumes depicting species relationships. Cardoso et al. (2015) <doi:10.1111/2041-210X.12310>.
Author: Pedro Cardoso [aut, cre], Stefano Mammola [aut], Francois Rigal [aut], Renato Hilario [aut], Jose Carvalho [aut]
Maintainer: Pedro Cardoso <pmcardoso@ciencias.ulisboa.pt>

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Package trade updated to version 0.8.6 with previous version 0.8.3 dated 2025-09-06

Title: Tools for Trade Practitioners
Description: A collection of tools for trade practitioners, including the ability to calibrate different consumer demand systems and simulate the effects of tariffs and quotas under different competitive regimes. These tools are derived from Anderson et al. (2001) <doi:10.1016/S0047-2727(00)00085-2> and Froeb et al. (2003) <doi:10.1016/S0304-4076(02)00166-5>.
Author: Charles Taragin [aut, cre]
Maintainer: Charles Taragin <ctaragin+trader@gmail.com>

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Package templr updated to version 0.2-4 with previous version 0.2-3 dated 2026-01-13

Title: MASCOTNUM / RT-UQ Algorithms Template Tools
Description: Helper functions for MASCOTNUM / RT-UQ <https://uq.math.cnrs.fr/> algorithm template, for design of numerical experiments practice: algorithm template parser to support MASCOTNUM specification <https://github.com/MASCOTNUM/algorithms>, 'ask & tell' decoupling injection (inspired by <https://search.r-project.org/CRAN/refmans/sensitivity/html/decoupling.html>) to use "crimped" algorithms (like uniroot(), optim(), ...) from outside R, basic template examples: Brent algorithm for 1 dim root finding and L-BFGS-B from base optim().
Author: Yann Richet [aut, cre]
Maintainer: Yann Richet <yann.richet@asnr.fr>

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Package linl updated to version 0.0.6 with previous version 0.0.5 dated 2023-01-11

Title: 'linl' is not 'Letter'
Description: A 'LaTeX' Letter class for 'rmarkdown', using the 'pandoc-letter' template adapted for use with 'markdown'.
Author: Dirk Eddelbuettel [aut, cre] , Aaron Wolen [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package eClosure updated to version 0.9.6 with previous version 0.9.5 dated 2026-06-01

Title: Methods Based on the e-Closure Principle
Description: Implements several methods for False Discovery Rate control based on the e-Closure Principle, in particular the Closed Benjamini-Hochberg, Closed e-Benjamini-Hochberg and Closed Benjamini-Yekutieli procedures.
Author: Jelle Goeman [aut, cre]
Maintainer: Jelle Goeman <j.j.goeman@lumc.nl>

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Package RPatternJoin (with last version 1.0.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2024-10-25 1.0.0

Permanent link
Package margEVT updated to version 0.2.0 with previous version 0.1.1 dated 2026-07-30

Title: Regularized Point Processes and Stochastic Marginalization for Extremes
Description: Implements a non-stationary extreme value analysis framework by coupling a covariate-driven Non-Homogeneous Poisson Process (NHPP) with Elastic-Net regularization and exact analytical gradients. Provides methodologies for estimating conditional return levels and unconditional (marginalized) return levels via parametric stochastic integration over Vector Autoregressive VAR(p) covariate trajectories, or non-parametric annual-block resampling. Temporal resolution and active-set tolerances are propagated consistently through fitting, marginalization, simulation, and validation. Methodologies are based on Villa (2026) <https://sabi.ufrgs.br/> "A Novel Regularized Point Process and Stochastic Marginalization Framework for Return Level Inference under Covariate-Driven Extremes" (Master's dissertation, Universidade Federal do Rio Grande do Sul).
Author: Rodrigo Fonseca Villa [aut, cre] , Flavio Ziegelmann [aut, ths]
Maintainer: Rodrigo Fonseca Villa <rodrigo03.villa@gmail.com>

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Permanent link

Package litReview updated to version 1.1.0 with previous version 1.0.0 dated 2026-08-07

Title: Summarizing Graphs for Literature Reviews
Description: Summarizes and visualizes categorical data extracted during literature reviews and evidence syntheses, starting from a data frame with one row per study. Generates publication-ready bar, stacked bar, histogram, waffle, donut, treemap, alluvial, trend, co-occurrence, 'UpSet', tree, and study-by-criteria matrix figures, together with world maps and formatted summary tables. Plot functions return standard 'ggplot2' objects that can be further customized, and an interactive 'Shiny' application is included for building figures without writing code. Aims to help researchers report study characteristics consistently across many publications.
Author: Sonsoles Lopez-Pernas [aut, cre, cph], Kamila Misiejuk [aut], Mohammed Saqr [aut]
Maintainer: Sonsoles Lopez-Pernas <sonsoles.lopez@uef.fi>

Diff between litReview versions 1.0.0 dated 2026-08-07 and 1.1.0 dated 2026-08-26

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Permanent link

Package jiebaRS updated to version 0.3.0 with previous version 0.2.0 dated 2026-08-04

Title: Chinese Text Segmentation, POS Tagging, and Keyword Extraction
Description: Provides fast Chinese text segmentation, keyword extraction via 'TF-IDF' and 'TextRank', and part-of-speech tagging, powered by a 'Rust' backend ('jieba-rs'). Supports custom dictionaries, user words, stop words, IDF files, and HMM models, with parallel batch processing of multiple strings. Serves as a modern, maintained replacement for the 'jiebaR' package.
Author: Hao Cheng [aut, cre, cph]
Maintainer: Hao Cheng <Yousa-Mirage@foxmail.com>

Diff between jiebaRS versions 0.2.0 dated 2026-08-04 and 0.3.0 dated 2026-08-26

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Package immundata updated to version 0.1.0 with previous version 0.0.7 dated 2026-04-04

Title: A Unified Data Layer for Large-Scale Single-Cell, Spatial and Bulk Immunomics
Description: Provides a unified data layer for single-cell, spatial and bulk T-cell and B-cell immune receptor repertoire data. Think AnnData or SeuratObject, but for AIRR data, a.k.a. Adaptive Immune Receptor Repertoire, VDJ-seq, RepSeq, or VDJ sequencing data.
Author: Vadim I. Nazarov [aut, cre]
Maintainer: Vadim I. Nazarov <support@immunomind.com>

Diff between immundata versions 0.0.7 dated 2026-04-04 and 0.1.0 dated 2026-08-26

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Package glydraw updated to version 0.9.0 with previous version 0.8.0 dated 2026-08-02

Title: Draw Beautiful Symbol Nomenclature for Glycans
Description: A 'ggplot2'-native plotting engine for drawing reproducible beautiful Symbol Nomenclature for Glycans (SNFG) glycan cartoons from glycan structure objects or text notations, with support for batch export, structural highlighting, and deep appearance customization. It follows the SNFG specification described at <https://www.ncbi.nlm.nih.gov/glycans/snfg.html>.
Author: Bin Fu [aut, cre, cph] , Xisong Feng [aut]
Maintainer: Bin Fu <23110220018@m.fudan.edu.cn>

Diff between glydraw versions 0.8.0 dated 2026-08-02 and 0.9.0 dated 2026-08-26

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Package betareg updated to version 3.2-6 with previous version 3.2-5 dated 2026-07-12

Title: Beta Regression
Description: Beta regression for modeling beta-distributed dependent variables on the open unit interval (0, 1), e.g., rates and proportions, see Cribari-Neto and Zeileis (2010) <doi:10.18637/jss.v034.i02>. Moreover, extended-support beta regression models can accommodate dependent variables with boundary observations at 0 and/or 1, see Kosmidis and Zeileis (2025) <doi:10.1093/jrsssc/qlaf039>. For the classical beta regression model, alternative specifications are provided: Bias-corrected and bias-reduced estimation, finite mixture models, and recursive partitioning for beta regression, see GrĂ¼n, Kosmidis, and Zeileis (2012) <doi:10.18637/jss.v048.i11>.
Author: Achim Zeileis [aut, cre] , Francisco Cribari-Neto [aut] , Bettina Gruen [aut] , Ioannis Kosmidis [aut] , Alexandre B. Simas [ctb] , Andrea V. Rocha [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

Diff between betareg versions 3.2-5 dated 2026-07-12 and 3.2-6 dated 2026-08-26

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Package rix updated to version 0.18.5 with previous version 0.18.2 dated 2026-02-18

Title: Reproducible Data Science Environments with 'Nix'
Description: Simplifies the creation of reproducible data science environments using the 'Nix' package manager, as described in Dolstra (2006) <ISBN 90-393-4130-3>. The included `rix()` function generates a complete description of the environment as a `default.nix` file, which can then be built using 'Nix'. This results in project specific software environments with pinned versions of R, packages, linked system dependencies, and other tools or programming languages such as Python or Julia. Additional helpers make it easy to run R code in 'Nix' software environments for testing and production.
Author: Bruno Rodrigues [aut, cre] , Philipp Baumann [aut] , David Watkins [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/625>), Jacob Wujiciak-Jens [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/62 [...truncated...]
Maintainer: Bruno Rodrigues <bruno@brodrigues.co>

Diff between rix versions 0.18.2 dated 2026-02-18 and 0.18.5 dated 2026-08-26

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Package musclesyneRgies updated to version 1.3.1 with previous version 1.2.5 dated 2022-07-19

Title: Extract Muscle Synergies from Electromyography
Description: Provides a framework to factorise electromyography (EMG) data. Tools are provided for raw data pre-processing, non negative matrix factorisation, classification of factorised data and plotting of obtained outcomes. In particular, reading from ASCII files is supported, along with wide-used filtering approaches to process EMG data. All steps include one or more sensible defaults that aim at simplifying the workflow. Yet, all functions are largely tunable at need. Example data sets are included.
Author: Alessandro Santuz [aut, cre]
Maintainer: Alessandro Santuz <alessandro.santuz@gmail.com>

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Package msma updated to version 3.2 with previous version 3.1 dated 2024-02-14

Title: Multiblock Sparse Multivariable Analysis
Description: Several functions can be used to analyze multiblock multivariable data. If the input is a single matrix, then principal components analysis (PCA) is implemented. If the input is a list of matrices, then multiblock PCA is implemented. If the input is two matrices, for exploratory and objective variables, then partial least squares (PLS) analysis is implemented. If the input is two lists of matrices, for exploratory and objective variables, then multiblock PLS analysis is implemented. Additionally, if an extra outcome variable is specified, then a supervised version of the methods above is implemented. For each method, sparse modeling is also incorporated. Functions for selecting the number of components and regularized parameters are also provided.
Author: Atsushi Kawaguchi [aut, cre]
Maintainer: Atsushi Kawaguchi <kawa_a24@yahoo.co.jp>

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Package GGIRread updated to version 1.0.10 with previous version 1.0.9 dated 2026-07-15

Title: Wearable Accelerometer Data File Readers
Description: Reads data collected from wearable acceleratometers as used in sleep and physical activity research. Currently supports file formats: binary data from 'GENEActiv' <https://activinsights.com/>, .bin-format from GENEA devices (not for sale), and .cwa-format from 'Axivity' <https://axivity.com>. Further, it has functions for reading text files with epoch level aggregates from 'Actical', 'Fitbit', 'Actiwatch', 'ActiGraph', and 'PhilipsHealthBand'. Primarily designed to complement R package GGIR <https://CRAN.R-project.org/package=GGIR>.
Author: Vincent T van Hees [aut, cre], Patrick Bos [aut] , Lena Kushleyeva [ctb], Jing Hua Zhao [ctb], Evgeny Mirkes [ctb], Dan Jackson [ctb], Jairo H Migueles [ctb], John Muschelli [ctb], Medical Research Council UK [cph, fnd], Accelting [cph, fnd]
Maintainer: Vincent T van Hees <v.vanhees@accelting.com>

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Package dtametaTMB updated to version 0.1.2 with previous version 0.1.1 dated 2026-07-26

Title: Diagnostic Test Accuracy Meta-Analysis using Template Model Builder
Description: Fits the hierarchical summary receiver operating characteristic (HSROC) model of Rutter and Gatsonis (2001) <doi:10.1002/sim.942>, the bivariate binomial-normal model of Reitsma et al. (2005) <doi:10.1016/j.jclinepi.2005.02.022>, the threshold-based bivariate time-to-event model of Hoyer et al. (2018) <doi:10.1002/jrsm.1273>, and the latent class extensions of Liu et al. (2015) <doi:10.1111/biom.12264> for diagnostic studies with an imperfect reference standard. Provides subgroup analyses, HSROC meta-regression, likelihood-ratio tests, summary ROC plots, and coupled forest plots.
Author: Claus Nowak [aut, cre]
Maintainer: Claus Nowak <claus.nowak@donau-uni.ac.at>

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Package basifoR updated to version 0.7.9 with previous version 0.7.8 dated 2026-07-02

Title: Retrieval and Processing of the Spanish National Forest Inventory
Description: Fetches, harmonizes, and analyses data from the Spanish National Forest Inventory for reproducible, design-aware forest inventory workflows. Computes tree- and stand-level metrics, applies sampling-based expansion factors, estimates volume, and supports extensible processing for external inventory designs with custom sampling schemes and volume equations. Spatial extensions can attach plot geometries, preserve geometry sidecars through metric workflows, and return georeferenced sf outputs for mapping and remote-sensing integration.
Author: Wilson Lara [aut, cre] , Cristobal Ordonez [aut] , Aitor Vazquez-Veloso [aut] , Felipe Bravo [aut]
Maintainer: Wilson Lara <wilarhen@gmail.com>

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Package APRScenario updated to version 0.0.4.2 with previous version 0.0.4.0 dated 2026-07-15

Title: Structural Scenario Analysis for Bayesian Structural Vector Autoregression Models
Description: Implements the scenario analysis proposed by Antolin-Diaz, Petrella and Rubio-Ramirez (2021) "Structural scenario analysis with SVARs" <doi:10.1016/j.jmoneco.2020.06.001>.
Author: Giovanni Lombardo [aut, cre], Tito Quadri [aut]
Maintainer: Giovanni Lombardo <giannilmbd@gmail.com>

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Package harmonydata (with last version 0.3.2) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2026-07-02 0.3.2
2025-04-20 0.3.1
2025-03-08 0.2.1
2023-10-19 0.1.1
2023-09-05 0.1.0

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Package EEAaq (with last version 1.0.3) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2026-02-10 1.0.3
2026-01-21 1.0.2
2025-03-20 1.0.1
2025-02-06 1.0.0
2023-08-23 0.0.3
2023-07-17 0.0.2
2023-05-29 0.0.1

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Package wcde (with last version 0.0.8) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2026-02-25 0.0.8
2024-02-13 0.0.7
2023-12-19 0.0.6
2022-06-06 0.0.5
2022-05-11 0.0.4
2021-10-30 0.0.3
2021-07-28 0.0.2
2021-06-23 0.0.1

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Package Qindex updated to version 0.2.1 with previous version 0.2.0 dated 2026-07-17

Title: A Legacy Package
Description: The author has retired from academic research. Accordingly, this package should not be considered a validated tool for use in peer-reviewed publications or as the basis for grant applications. Backward compatibility with user-code published in <doi:10.1186/s12859-023-05408-8> and <doi:10.1016/j.labinv.2023.100158> is not maintained in versions >= 0.4.0 (June 2026) of this package. The authors of those publications are the appropriate contacts for reproducibility inquiries.
Author: Tingting Zhan [aut, cre]
Maintainer: Tingting Zhan <tingtingzhan@gmail.com>

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